Larger A Bank And Asymmetric Information Essay

Question:

Discuss about the Larger a Bank the Better is its Ability to Diversify.

Answer:

The statement to assess is the capability of larger banks. The topic suggests that larger banks should not be limited by the regulators as the larger pool of the asset means diversification of the portfolio. From the regulators perspective it means higher risk which has potential to engulf lot out of financial system.

Large banking demands are a key business driver for regulator decisions in this industry sector. A large bank uses a broad range of technology-centric capabilities that enable new methods of interaction and service delivery to augment customer experience and potentially transform the business (Admati, 2014).

These capabilities are supported by a robust, dynamic and accessible large infrastructure and an open banking system that transforms the analog environment. However, for many banks, their application portfolio represents transactional interaction support that matches consumer expectations of banking from decades past (Khairi, 2015).

The demands of today's banking customers transcend ATM ubiquity and the convenience of branch banking locations. Traditional banks that aspire to compete with disruptive financial technology firms have to focus on the formerly defined mid-office and back-office technologies with specific attention on supporting hardware platforms.

The challenge for many of today's modernization projects is not simply a change in technology, but often a fundamental restructuring of application architectures and deployment models. Mainframe hardware and software architectures have defined the structure of applications built on this platform for the last 50 years. Tending toward large-scale, monolithic systems that are predominantly customized, they represent the ultimate in size, complexity, reliability and availability.

Today's modern computing environments represent a very different model. Commodity x86, scale-out environments define a different set of technologies, database management system (DBMS) platforms and architectures. Modernizing legacy systems from a mainframe architecture to a distributed one is a major challenge for any large-scale financial institution (Grubel?2014).

There is a distinct retreat by bank CIOs from high-cost, complex mid-office and back-office environments to easier-accessed functionality promoted by component-based solutions. Simplification, agility and operational efficiency are the primary drivers behind banks' efforts to abandon legacy solutions and past deployment practices. While many organizations that are dependent on mainframe architectures could have modernized their existing portfolios over time in an evolutionary fashion, many chose to avoid the risk of change and preserve their extant systems, continuing to leverage their current staff resources. As the reality of the demographic shift of baby boomers became clearer to many organizations, this risk-averse option is becoming more problematic (Laeven?2013). Now, the ability to attack such a massive application portfolio and restructure it for modern languages and platforms is seen as a great risk. The procrastination of yesterday's regulator organizations is now driving different modernization decisions, including moving to commercially available packaged solutions for many use cases, including core banking. These capabilities are supported by a robust, dynamic and accessible large infrastructure and an open banking system that transforms the analog environment. However, for many banks, their application portfolio represents transactional interaction support that matches consumer expectations of banking from decades past (Schludi, 2015).


In the face of new bank entrants, financial institutions are under increasing pressure to formulate and execute large banking strategies. Designed to transform traditional banking models, these strategies are predominantly technology-supported initiatives impacting customer-facing channels through to the back office. As bank CEOs expect large revenues to dramatically expand to 47% by 2019, CIO-led large banking programs are expected to have a significant impact on upcoming regulator decisions (White, 2014).

Accommodating new areas of regulator investment for large banking have to be offset with corresponding reductions in tactical, regulator commodity spending. Many banks are pursuing core banking renewal to simultaneously reverse traditional regulator spending patterns and replace them with lower-cost, agile platforms. This is easier said than done, as many of the existing regulator systems in support of the overall bank are mission-critical and demand high availability, reliability and performance. Shifting from scale-up architectures (such as the mainframe) to scale-out environments (commonly x86) requires significant investment in understanding the existing systems in great detail, but also a rethinking of the implementation in a modern, multiserver world. Banks need to be able to justify the cost and risk of any modernization project. This can be difficult in the face of a well-proven, time-tested portfolio that has represented the needs of the banking system for decades. However, the demands for modern banking solutions, which are increasingly targeting a different demographic, require extensive change to the existing systems. The alternative has been to add layers of technology on top of the existing legacy systems, which tend to increase cost and complexity (Reinhart, 2013).

Many modernization inquiries from our customers are not simply about an aging technology stack, or even aging workforce, but rather about fundamental changes in the business. Banking CIOs should embrace a large-first, outside-in thought process when modernizing their legacy portfolios. Modern consumers of banking have expectations set by their experiences with Amazon, Google or Facebook. These expectations are less predictable than in the past and make it more difficult to instantiate a business process in code and expect that code to last for decades, as has been the case for much of the extant banking portfolio (Martins, 2014). Today's systems must be built to change, and not to last!

Dependent on a bank's market strategy and segmentation, organizations are increasingly considering broad-based, functional, packaged solutions for existing systems of record, or the usage of commercial off-the-shelf coarse-grain components (BPM, BI query, analytics, report writers) to implement their replacement systems. In support of large banking ambitions, many industry CIOs aim to migrate resources from commodity systems (such as core banking) and redirect them to differentiating technologies that directly impact the customer experience.

References:

  • Admati, A., & Hellwig, M. (2014).The bankers' new clothes: What's wrong with banking and what to do about it. Princeton University Press
  • Schludi, M. H., May, S., Gr?sser, F. A., Rentzsch, K., Kremmer, E., K?pper, C., ... & Edbauer, D. (2015). Distribution of dipeptide repeat proteins in cellular models and C9orf72 mutation cases suggests link to transcriptional silencing.Acta neuropathologica, 130(4), 537-555
  • Khairi, M. S., & Baridwan, Z. (2015). An empirical study on organizational acceptance accounting information systems in Sharia banking.The International Journal of Accounting and Business Society, 23(1), 97-122
  • Grubel, H. G. (2014). A theory of multinational banking.PSL Quarterly Review, 30(123)
  • Reinhart, C. M., & Rogoff, K. S. (2013). Banking crises: an equal opportunity menace.Journal of Banking & Finance, 37(11), 4557-4573
  • White, E. N. (2014).The regulation and reform of the American banking system, 1900-1929. Princeton University Press
  • Laeven, L., & Valencia, F. (2013). Systemic banking crises database.IMF Economic Review, 61(2), 225-270
  • Martins, C., Oliveira, T., & Popovi?, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application.International Journal of Information Management, 34(1), 1-13

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